Program with the intent to detect Atmospheric Blocking structures
This implementation is a 2 dimensional addaptation of the algorithm presented by Barnes et al., (2012), to detect atmospheric blockings structures in two atmospheric fields, Potential Temperature at Dynamical Tropopause, Pelly & Hoskins, (2012), Berrisford et al., (2007) and Geopotential Height in the Middle Troposphere, Tibaldi & Molteni, (1990).
The fortran routines presented here were used to assess atmospheric blockings in the master dissertation of Campos, J.L.P.S., 2014.
- (1) Before runnning you need to set up with input/output directories and begin and end dates in the file config.fortran.txt in folder pwd/config/
- (2) The fortran95 version of this implementation is intended to read monthly netcdf data issued 6 by 6 hours. For other configurations, you must to addapt the main program.
- (3) You need to install the netcdf libraries in your UNIX system before running.
- (4) The compile options for fortran95 implementation is in file main_f95.sh
#!/bin/bash FC="gfortran" fflags="-fdefault-real-8 -fconvert=big-endian -frecord-marker=4 -w -O3" LIBNETCDF="-I/usr/include/ -L/usr/lib -lnetcdf -lnetcdff" pwdd=`pwd` $FC $fflags -c src_fortran/Blocked_Flow_Index_new_v2.f95 $LIBNETCDF $FC $fflags -c main.f95 $LIBNETCDF $FC $fflags main.f95 src_fortran/Blocked_Flow_Index_new_v2.f95 -o a.out $LIBNETCDF -I/$pwdd/src_fortran/ ./a.out
In summer season over South America, when a blocking event is set over the South Atlantic coast, it is expected a poleward displacement of the climatological humidity conveyour belt, the convergence zone, leading to droughts over the most populated south american megalopolis, the São Paulo - Rio de Janeiro region and wetness over other megalopolis region, the Buenos Aires/Mar del La Plata region. Beyond the impacts in water supply and agriculture, hydroeletricity and renewable energy markets are strong impacted as well. Long lasting droughts and wetness can lead to a great volatility in the energy price leading business to bankrupticy if the blocking is not forecasted. So, the automatic identification of blockings associated with weather forecast products can help in the decision making by energy traders and civil defense professionals. This repository aims to provide a tool capable of identify atmospheric blockings.
In middle and high latitudes, the upper level winds generally flows from west to east, forming a jet stream due to strengthening of meridional temperature gradient Holton et al. 2016. When this flow cross some topographical barrier (like the Rokies or the Himalayas) or are influenced by stationary Rossby Waves, it gains potential vorticiy and starts to meander, generating circulation patterns in the form of high and low pressure anomalies. When the configuration of this anomalies leads to an eastward flux opposing the jet stream and lasting more than 3 or 5 days, we call these events as atmospheric blocking (Tibaldi & Molteni, 1990).
In an atmospheric dynamics framework, atmospheric blocking events can be seen as Rossby Wave breaking events (Pelly & Hoskins, 2012). Strong convection in tropics and in convergence zones (both leading to upper level divergence) can generate vorticity anomalies due to latent heat loss to the atmosphere, exciting Rossby Waves, which propagates in an arch like trajectory from tropics to extratropics to tropics, generating interspersed anomalies of positive and negative vorticity along its trajectory. High pressure systems acts as a Rossby Waves sink, in other hand low pressure systems acts as Rossby Waves sources (Takaya & Nakamura, 2000), when the energy is vanished, the "tip" of the Rossby Wave decays in the form of a dipole like pattern, where the blocking high is poleward to a cuttoff low (both barotropic systems), generating an eastward flux, the blocked flux.
In classical works (Tibaldi & Molteni, 1990), there were identified two types of atmospheric blockings structures, the omega blocking type, depicted in fig.1a-c and the dipole blocking type, depicted in fig.1d-h. Therefore, the purpose of these repository is to provide a set of routines capable to identify these kinds of structures.
Before formulating an algorithm to detect atmospheric blockings, some quantities must be computed, such as the meridional gradient of potential temperature or geopotential height, for the potential temperature at the dynamical tropopause (\theta) and geopotential height at 500hPa level (Z) respectivelly, as defined bellow:
Equations 1 and 2 represent the quantities to be computed with the geopotential height and potential temperature respectivelly. To a flow be considered as a blocked flow, the following criteria must be verified, we call this of Instantaneous Blocked Latitude (IBL).
After the IBL's were grouped into a Group of Instantaneous Blocked Latitudes (GIBLs) and it was verified the GIBLs' persistence, it they persisted at least T days it will be classified as blocking, otherwise it will not. An algorithm based on Barnes et al., (2012) for blocking detection is presented bellow.
The red dotted line shows the atmospheric blocking region as detected by the algorithm with the quantities computed in eq.1 and eq.2.
